The study examines to what extent weak labor unions and an abundance of labor have a negative effect on less developed countries terms of trade, as hypothesized by Hans Singer (1950) and Rául Prebisch (1950). Using a sample from panel data for 74 less developed countries during the period 1980 – 2010 in OLS-regressions with fixed effects, I find some evidence that weak labor unions and abundance of labor is negatively correlated with the terms of trade, which could be interpreted in favor of the Prebisch-Singer hypothesis. The marginal effect of an abundance of labor also appears to have less negative impact on the terms of trade as labor unions grow stronger.

Interaction and marginal effects are often an important concern, especially when variables are allowed to interact in a nonlinear model. In a linear model, the interaction term, representing the interaction effect, is the impact of a variable on the marginal effect of another variable. In a nonlinear model, however, the marginal effect of the interaction term is different from the interaction effect. This report provides a general derivation of both effects in a nonlinear model and a linear model to clearly illustrate the difference. These differences are then demonstrated with empirical data. The empirical study shows that the corrected interaction effect in an ordered logit or probit model is substantially different from the incorrect interaction effect produced by the margins command in Stata. Based on the correct formulas, this report verifies that the interaction effect is not the same as the marginal effect of the interaction term. Moreover, we must be careful when interpreting the nonlinear models with interaction terms in Stata or any other statistical software package. / text

This thesis contributes to the research area of causal inference, where estimation of the effect of a treatment on an outcome of interest is the main objective. Some aspects of the estimation of average causal effects in observational studies in general, and case-control studies in particular, are explored. An important part of estimating causal effects in an observational study is to control for covariates. The first paper of this thesis concerns the selection of minimal covariate sets sufficient for unconfoundedness of the treatment assignment. A data-driven implementation of two covariate selection algorithms is proposed and evaluated. A common sampling scheme in epidemiology, and when investigating rare events, is the case-control design. In the second paper we study estimators of the marginal causal odds ratio in matched and independent case-control designs. Estimators that, under a logistic regression model, utilize information about the known prevalence of being a case is examined and compared through simulations. The third paper investigates the particular situation where case-control sampled data is reused to estimate the effect of the case-defining event on an outcome of interest. The consequence of ignoring the design when estimating the average causal effect is discussed and a design-weighted matching estimator is proposed. The performance of the estimator is evaluated with simulation experiments, when matching on the covariates directly and when matching on the propensity score. The last paper studies the effect of type 1 diabetes mellitus (T1DM) on school achievements using data from the Swedish Childhood Diabetes Register, a population-based incidence register. We apply theoretical results from the second and third papers in the estimation of the average causal effect within the T1DM population. A matching estimator that accounts for the matched case-control design is used.

Fuel reduction treatments are management activities implemented to reduce the quantity of hazardous fuels in forests to decrease the probability of severe and intense wildfires. As nonindustrial private forest (NIPF) landowners own most forests (77%) in Mississippi, their involvement is essential for effective and coordinated fuel reduction treatments to achieve a large-scale wildfire hazard reduction. However, NIPF landowner attitudes towards wildfire risk and mitigation activities implemented to reduce wildfire risk are not well understood. This study determined attitudes of NIPF landowners towards wildfires, current trends in implementation of fuel reduction treatments, socioeconomic and geospatial factors affecting treatment implementation, and landowner willingness to pay (WTP) for prescribed burning. Data were collected via a mail survey of NIPF landowners and public sources including Mississippi Forestry Commission and National Land Cover Database. The contingent valuation method (CVM) was used to quantify the WTP for prescribed burning. Data were analyzed using seemingly unrelated and binary probit, and binary logit models. Approximately 68% of landowners were concerned about wildfires, but only 45% implemented hazardous fuel reduction treatments. Prescribed burning was the most commonly implemented and the least costly treatment. Furthermore, only 30% of landowners were likely to implement fuel reduction treatments in the next five years. Past implementation of treatments, concern about property damages due to wildfires, familiarity with wildfire prevention and mitigation programs, size of forest land owned, ecological services ownership objectives, past experience with wildfires, and motivation from neighbors’ implementation of treatments were positively associated with the likelihood of implementing fuel reduction treatments in the next five years. Landowners were willing to pay from $14.70 to $66.86 per acre, with an average of $41.39 per acre, for implementing prescribed burning on their forest land. The payment amount was negatively related to WTP, whereas education level, tolerance of smoke from prescribed burns, concern about property damages due to wildfires, and consideration of liability issues as an important factor were positively related. Results will help better understand NIPF landowner wildfire mitigation activities and associated social and geospatial factors, and aid in the development of more effective strategies and resource allocation for wildfire prevention and mitigation.

Food safety problems have gained national attention, and food recall is one of the most important indications of this concern. Third-party certifications have become a popular way to improve the safety and quality of products for consumers. Publications related to third-party certification usually focus on the motives and benefits of a particular certification. However, to date, no existing research investigates the effects of food recalls on certification adoption. This study uses Probit models with a binary endogenous explanatory variable to examine the relationship between food recalls and third-party certification, based on recalls occurring between January 1, 2015 and February 18, 2016. Marginal effects are used to interpret the impact of recalls and companies’ annual net sales on third-party certification adoption. Results reveal that past recalls significantly affect a firm’s likelihood of certification adoption.

L’objectif de cette thèse consiste en l’élaboration de deux méthodologies visant à révéler des effets jusqu’alors masqués en modélisation décisionnelle. Dans la première partie, nous cherchons à mettre en œuvre une méthode d’analyse locale des critères de choix dans un contexte de choix binaires. Dans une seconde partie, nous mettons en avant les effets de génération dans l’étude des comportements de choix. Dans les deux parties, notre démarche de recherche combine de nouveaux outils d’analyse prédictive (Support Vector Machines, FANOVA, PLS) aux outils traditionnels de statistique inférentielle, afin d’enrichir les résultats habituels par des informations complémentaires sur les effets masqués que constituent les effets locaux dans les fonctions de choix binaires, et les effets de génération dans l’analyse temporelle des comportement de choix. Les méthodologies proposées, respectivement nommées AEL et APC-PLS, sont appliquées sur des cas réels, afin d’en illustrer le fonctionnement et la pertinence. / The objective of this thesis is the development of two methodologies to reveal previously hidden effects in decision modeling. In the first part, we try to implement a method of local analysis in order to select criteria in the context of binary choices. In a second part, we highlight the effects of generations in the study of consumer behavior. In both parts, our research approach combines new predictive analytical tools (such as Support Vector Machines, FANOVA, PLS) to traditional tools of inferential statistics, to enrich the usual results by additional on the masked effects, which are the local effects in the binary choice functions, and the effects of generation in temporal choice behavior analysis.The proposed methodologies, respectively named AEL and APC- PLS are both applied to real cases in order to illustrate their operation and relevance.

Over that past three decades, power sector reform has been a key pillar of policy agendas in more than half of the countries across the world. This thesis specifically concerns the empirical investigation of the economic performance of the international electricity generation industry. Drawing on the stochastic frontier analysis techniques, the thesis considers the influence of reform as exogenous factors in shifting frontier technology as well as shaping inefficiency function directly -determinants and heteroscedasticity variables. The first essay uses an extensive panel dataset of 91 countries over the period 1980 to 2010 to measure the impact of deregulation on efficiency and total productivity growth using stochastic input distance frontier (SIDF). Three specific issues are addressed in the first essay: (1) the relationship between deregulation and technical efficiency, (2) the extent of the rank correlation of the country intercepts with deregulation via their position on the frontier, (3) the trend of total factor productivity and its components. We establish a positive impact of deregulation on efficiency and some compelling evidence suggesting that the country intercepts equally account for the influence of deregulation aside efficiency. In particular, the technical efficiency index from the first paper reveals that most OECD European countries are consistently efficient. Building on this finding, the second essay investigates the performance in term of cost efficiency for electricity generation in OECD power sector while accounting for the impact of electricity market product regulatory indicators. Empirical models are developed for the cost function as a translog form and analysed using panel data of 25 countries during the period 1980 to 2009. We show that it is necessary to model latent country-specific heterogeneity in addition to time-varying inefficiency. The estimated economies of scale are adjusted to take account of the importance of the quasi-fixed capital input in determining cost behaviour, and adjusted economies of scale are verified for the OECD generation sector. The findings suggest there is a significant impact of electricity market regulatory indicators on cost. Cost complementarity between generation and emissions found to be significant, indicating the possibility of reducing emissions without necessarily reducing electricity generation. Finally, the third essay examines the performance of electric power industry s using consistent state-level electricity generation dataset for the US contiguous states from 1998-2014. We estimate stochastic production frontier for five competing models in order to identify the determinants of technical inefficiency and marginal effects. We find evidence of positive impacts of deregulation on technical efficiency across the models estimated. Our preferred model shows that deregulated states are more efficient in electricity generation than non-deregulated states. The result of the marginal effects shows that deregulation has a positive and monotonic effect on the technical efficiency.

Submitted by Kleber Osman (kleber.osman@icloud.com) on 2018-03-02T01:11:37Z No. of bitstreams: 1 Dissertação - Kleber Osman.pdf: 857853 bytes, checksum: 51c38d1dfdb2e92c87e2269bcc638896 (MD5) / Rejected by Thais Oliveira (thais.oliveira@fgv.br), reason: Prezado Kleber, boa noite! Para que possamos aprovar seu trabalho, será necessário que faça somente uma alteração: - Na capa, o nome "GETULIO" não tem acento. Por gentileza alterar e submeter novamente. Obrigada! on 2018-03-06T00:00:13Z (GMT) / Submitted by Kleber Osman (kleber.osman@icloud.com) on 2018-03-06T02:15:42Z No. of bitstreams: 1 Dissertação - Kleber Osman.pdf: 861905 bytes, checksum: 3478b1be8a0bd0efd15781f0c21be7cd (MD5) / Approved for entry into archive by Thais Oliveira (thais.oliveira@fgv.br) on 2018-03-06T19:29:17Z (GMT) No. of bitstreams: 1 Dissertação - Kleber Osman.pdf: 861905 bytes, checksum: 3478b1be8a0bd0efd15781f0c21be7cd (MD5) / Made available in DSpace on 2018-03-07T13:05:15Z (GMT). No. of bitstreams: 1 Dissertação - Kleber Osman.pdf: 861905 bytes, checksum: 3478b1be8a0bd0efd15781f0c21be7cd (MD5) Previous issue date: 2018-02-06 / A crise previdenciária vivenciada no decorrer dos últimos anos mostrou que seus impactos não se restringem ao desequilíbrio das contas públicas devido ao aumento dessas despesas obrigatórias, mas também efeitos sociais e econômicos negativos podem atingir toda a economia brasileira. Diante disso, esforços se direcionaram na tentativa de encontrar uma alternativa que permita desonerar as contas públicas para evitar uma crise na economia local, assim como garantir que os aposentados mantenham a mesma renda frente ao salário recebido anteriormente à aposentadoria. Neste sentido, este estudo investiga o perfil dos investidores em previdência privada, visando detectar as principais características que os diferenciam. A análise do perfil dos indivíduos que contribuem para planos de previdência privada permite que políticas de incentivo a este produto sejam melhores desenhadas e, possibilita à iniciativa privada o seu direcionamento ao público-alvo de forma mais eficiente – uma vez reveladas as variáveis socioeconômicas de maior relevância. O método utilizado na indicação desses fatores baseia-se na estimação LOGIT, que tem como objetivo principal auferir quais são as variáveis com maiores ganhos marginais que afetam a probabilidade do indivíduo participar de plano de previdência privada. E, com base nos resultados, constatou-se que as variáveis 'educação' e 'renda' são preponderantes para a inscrição do indivíduo em plano de previdência privada. / The social security crisis experienced in recent years has shown that its impacts are not restricted to the imbalance of public accounts due to the increase in these compulsory expenses, but also negative social and economic effects can affect the entire Brazilian economy. In the face of this, efforts were directed towards finding an alternative that would allow public accounts to be discharged to avoid a crisis in the local economy, as well as ensuring that retirees maintain the same income against the salary received prior to retirement. In this sense, this study investigates the profile of private pension investors in order to detect the main characteristics that differentiate them. The analysis of the profile of individuals contributing to private pension plans allows policies to encourage this product to be better designed and allows the private sector to target the target public more efficiently - once the socioeconomic variables of greater relevance. The method used to indicate these factors is based on the LOGIT estimation, whose main objective is to determine which are the variables with the greatest marginal gains that affect the probability of the individual participating in a private pension plan. And, based on the results, it was verified that the variables 'education' and 'income' are preponderant for the inscription of the individual in private pension plan.

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